Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis: A Systematic Review

Chen, Zhiyi, Liu, Xuerong, Yang, Qingwu, Wang, Yan-Jiang, Miao, Kuan, Gong, Zheng, Yu, Yang, Leonov, Artemiy +3 more·2023·JAMA Network Open

Cites (614)

Items 201–400 of 572

  1. Investigating the predictive value of different resting-state functional MRI parameters in obsessive-compulsive disorder
    Xuan Bu, Xinyu Hu, Lianqing Zhang, Bin Li, Ming Zhou, Lu Lu, Xiaoxiao Hu, Hailong Li, Yanchun Yang, Wanjie Tang et al. · 2019 · Translational Psychiatry
  2. Abnormal regional homogeneity as a potential imaging biomarker for adolescent-onset schizophrenia: A resting-state fMRI study and support vector machine analysis
    Shuai Wang, Yan Zhang, Luxian Lv, Renrong Wu, Xiaoduo Fan, Jingping Zhao, Wenbin Guo · 2017 · Schizophrenia Research
  3. Multi-site clustering and nested feature extraction for identifying autism spectrum disorder with resting-state fMRI
    Nan Wang, Dongren Yao, Lizhuang Ma, Mingxia Liu · 2021 · Medical Image Analysis
  4. Extracting biomarkers of autism from MEG resting-state functional connectivity networks
    Vassilis Tsiaras, Panagiotis G. Simos, Roozbeh Rezaie, Bhavin R. Sheth, Eleftherios Garyfallidis, Eduardo M. Castillo, Andrew C. Papanicolaou · 2011 · Computers in Biology and Medicine
  5. Spectral features based convolutional neural network for accurate and prompt identification of schizophrenic patients
    Kuldeep Singh, Sukhjeet Singh, Jyoteesh Malhotra · 2020 · Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine
  6. Automated detection of schizophrenia using optimal wavelet-based $$l_1$$ norm features extracted from single-channel EEG
    Manish Dev Sharma, U. Rajendra Acharya · 2021 · Cognitive Neurodynamics
  7. Functional connectivity of major depression disorder using ongoing EEG during music perception
    Wenya Liu, Chi Zhang, Xiaoyu Wang, Jing Xu, Yi Chang, Tapani Ristaniemi, Fengyu Cong · 2020 · Clinical Neurophysiology
  8. Identifying Individuals with Antisocial Personality Disorder Using Resting-State fMRI
    Yan Tang, Weixiong Jiang, Jian Liao, Wei Wang, Aijing Luo · 2013 · PLoS ONE
  9. Multivariate neuroanatomical classification of cognitive subtypes in schizophrenia: A support vector machine learning approach
    Ian C. Gould, Alana M. Shepherd, Kristin R. Laurens, Murray J. Cairns, Vaughan J. Carr, Melissa J. Green · 2014 · NeuroImage Clinical
  10. ADHD classification by a texture analysis of anatomical brain MRI data
    Che-Wei Chang, Chien‐Chang Ho, Jyh‐Horng Chen · 2012 · Frontiers in Systems Neuroscience
  11. Use of deep learning to detect personalized spatial-frequency abnormalities in EEGs of children with ADHD
    He Chen, Yan Song, Xiaoli Li A · 2019 · Journal of Neural Engineering
  12. Generalizable brain network markers of major depressive disorder across multiple imaging sites
    Ayumu Yamashita, Yuki Sakai, Takashi Yamada, Noriaki Yahata, Akira Kunimatsu, Naohiro Okada, Takashi Itahashi, Ryuichiro Hashimoto, Hiroto Mizuta, Naho Ichikawa et al. · 2020 · PLoS Biology
  13. Multimodal Discrimination of Schizophrenia Using Hybrid Weighted Feature Concatenation of Brain Functional Connectivity and Anatomical Features with an Extreme Learning Machine
    Muhammad Naveed Iqbal Qureshi, Jooyoung Oh, Dongrae Cho, Hang Joon Jo, Boreom Lee · 2017 · Frontiers in Neuroinformatics
  14. Support vector machine-based classification of first episode drug-naïve schizophrenia patients and healthy controls using structural MRI
    Yuan Xiao, Zhihan Yan, Youjin Zhao, Tao Bo, Huaiqiang Sun, Fei Yue Li, Yao Li, Wenjing Zhang, Chandan Shah, Jieke Liu et al. · 2017 · Schizophrenia Research
  15. Diagnosis of Autism Spectrum Disorders in Young Children Based on Resting-State Functional Magnetic Resonance Imaging Data Using Convolutional Neural Networks
    Maryam Akhavan Aghdam, Arash Sharifi, Mir Mohsen Pedram · 2019 · Journal of Imaging Informatics in Medicine
  16. Single Volume Image Generator and Deep Learning-Based ASD Classification
    Md Rishad Ahmed, Yuan Zhang, Omer T. Inan, Hongen Liao · 2020 · IEEE Journal of Biomedical and Health Informatics
  17. Machine learning prediction models in orthopedic surgery: A systematic review in transparent reporting
    Olivier Quinten Groot, Paul T. Ogink, Amanda Lans, Peter K. Twining, Neal D. Kapoor, William DiGiovanni, Bas J. J. Bindels, Michiel E. R. Bongers, Jacobien H. F. Oosterhoff, Aditya V. Karhade et al. · 2021 · Journal of Orthopaedic Research®
  18. Pattern recognition analyses of brain activation elicited by happy and neutral faces in unipolar and bipolar depression
    Janaı́na Mourão-Miranda, Jorge Almeida, Stefanie Hassel, Letícia Oliveira, Amelia Versace, André F. Marquand, João Ricardo Sato, Michael John Brammer, Mary Louise Phillips · 2012 · Bipolar Disorders
  19. Can we accurately classify schizophrenia patients from healthy controls using magnetic resonance imaging and machine learning? A multi-method and multi-dataset study
    Julie L. Winterburn, Aristotle N. Voineskos, Gabriel A. Devenyi, Eric Plitman, Camilo de la Fuente‐Sandoval, Nikhil Bhagwat, Ariel Graff‐Guerrero, Jo Knight, M. Mallar Chakravarty · 2017 · Schizophrenia Research
  20. Machine learning multivariate pattern analysis predicts classification of posttraumatic stress disorder and its dissociative subtype: a multimodal neuroimaging approach
    Nicholson, Andrew A., Densmore, Maria, McKinnon, Margaret C., Neufeld, Richard W.J., Frewen, Paul A., Théberge, Jean, Jetly, Rakesh, Richardson, J. Donald, Lanius, Ruth A. · 2019 · Psychological Medicine
  21. A hybrid decision support system for automatic detection of Schizophrenia using EEG signals
    Smith K. Khare, Varun Bajaj · 2021 · Computers in Biology and Medicine
  22. Classifying social anxiety disorder using multivoxel pattern analyses of brain function and structure
    Andreas Frick, Malin Gingnell, André F. Marquand, Katarina Howner, Håkan Fischer, Marianne Kristiansson, Steven Williams, Mats Fredrikson, Tomas Furmark · 2013 · Behavioural Brain Research
  23. Translational machine learning for psychiatric neuroimaging
    Martin Walter, Sarah Alizadeh, Hamidreza Jamalabadi, Ulrike Lueken, Udo Dannlowski, Henrik Walter, Sebastian Olbrich, Lejla Čolić, Joseph P. Kambeitz, Nikolaos Koutsouleris et al. · 2018 · Progress in Neuro-Psychopharmacology and Biological Psychiatry
  24. An EEG-based machine learning method to screen alcohol use disorder
    Wajid Mumtaz, Pham Lam Vuong, Likun Xia, Aamir Saeed Malik, Rusdi Bin Abd Rashid · 2016 · Cognitive Neurodynamics
  25. Random forest based classification of alcohol dependence patients and healthy controls using resting state MRI
    Xi Zhu, Xiaofei Du, Mike Kerich, Falk W. Lohoff, Reza Momenan · 2018 · Neuroscience Letters
  26. Supervised machine learning for diagnostic classification from large-scale neuroimaging datasets
    Pradyumna Lanka, D. Rangaprakash, Michael N. Dretsch, Jeffrey S. Katz, Thomas S. Denney, Gopikrishna Deshpande · 2019 · Brain Imaging and Behavior
  27. Convergent and Divergent Functional Connectivity Patterns in Schizophrenia and Depression
    Yang Yu, Hui Shen, Ling‐Li Zeng, Qiongmin Ma, Dewen Hu · 2013 · PLoS ONE
  28. DISCRIMINATION OF SCHIZOPHRENIA AUDITORY HALLUCINATORS BY MACHINE LEARNING OF RESTING-STATE FUNCTIONAL MRI
    Darya Chyzhyk, M. Graña, D. Öngür, A. Shinn · 2015 · International Journal of Neural Systems
  29. Multivariate pattern analysis of DTI reveals differential white matter in individuals with obsessive‐compulsive disorder
    Fei Yue Li, Xiaoqi Huang, Wanjie Tang, Yanchun Yang, Bin Li, Graham John Kemp, Andrea Mechelli, Qiyong Gong · 2013 · Human Brain Mapping
  30. Multi-modal, Multi-measure, and Multi-class Discrimination of ADHD with Hierarchical Feature Extraction and Extreme Learning Machine Using Structural and Functional Brain MRI
    Muhammad Naveed Iqbal Qureshi, Jooyoung Oh, Beomjun Min, Hang Joon Jo, Boreom Lee · 2017 · Frontiers in Human Neuroscience
  31. Quantitative Identification of Major Depression Based on Resting-State Dynamic Functional Connectivity: A Machine Learning Approach
    Baoyu Yan, Xiaopan Xu, Mengwan Liu, Kaizhong Zheng, Jian Liu, Jianming Li, Wei Lei, Binjie Zhang, Hongbing Lu, Baojuan Li A · 2020 · Frontiers in Neuroscience
  32. Using resting state functional MRI to build a personalized autism diagnosis system
    Omar Dekhil, Hassan Hajjdiab, Ahmed M. Shalaby, Mohamed Talaat Ali, Babajide Odunitan Ayinde, Andy Switala, Aliaa Elshamekh, Mohammed Asaad Ghazal, Robert S. Keynton, Gregory Neal Barnes et al. · 2018 · PLoS ONE
  33. Classifying adolescent attention-deficit/hyperactivity disorder (ADHD) based on functional and structural imaging
    Iannaccone, Reto, Hauser, Tobias U., Ball, Juliane, Brandeis, Daniel, Walitza, Susanne, Brem, Silvia · 2015 · European Child & Adolescent Psychiatry
  34. Evaluation of Pattern Recognition and Feature Extraction Methods in ADHD Prediction
    João Ricardo Sato, Marcelo Q. Hoexter, André Fujita, Luís Augusto Rohde · 2012 · Frontiers in Systems Neuroscience
  35. Characterization of groups using composite kernels and multi-source fMRI analysis data: Application to schizophrenia
    Eduardo Castro, Manel Martínez‐Ramón, Godfrey D. Pearlson, Jing Sui (Beijing Normal University), my correct affiliation is beijing normal university, not Qingdao University of Science and Technology, please correct the current affiliation. Thank you, Vince D. Calhoun · 2011 · NeuroImage
  36. Functional brain dynamic analysis of ADHD and control children using nonlinear dynamical features of EEG signals
    Shiva Khoshnoud, Mohammad Ali Nazari, Mousa Shamsi · 2017 · Journal of Integrative Neuroscience
  37. Aberrant Functional Network Connectivity as a Biomarker of Generalized Anxiety Disorder
    Jian-Ping Qiao, Anning Li, Chongfeng Cao, Zhi-Shun Wang, Jian-De Sun, Guangrun Xu · 2017 · Frontiers in Human Neuroscience
  38. Classification of schizophrenia and normal controls using 3D convolutional neural network and outcome visualization
    Kanghan Oh, Woo‐Sung Kim, Guangfan Shen, Yan Hong Piao, Nam‐In Kang, Il-Seok Oh, Young‐Chul Chung · 2019 · Schizophrenia Research
  39. Multisite Autism Spectrum Disorder Classification Using Convolutional Neural Network Classifier and Individual Morphological Brain Networks
    Jingjing Gao, Mingren Chen, Yuanyuan Li, Ya-Chun Gao, Yanling Li, Shi‐Min Cai, Jiaojian Wang · 2021 · Frontiers in Neuroscience
  40. Resting-State Connectivity Biomarkers of Cognitive Performance and Social Function in Individuals With Schizophrenia Spectrum Disorder and Healthy Control Subjects
    Joseph D. Viviano, Robert W. Buchanan, Navona Calarco, James M. Gold, George Foussias, Nikhil Bhagwat, Laura Stefanik, Colin S. Hawco, Pamela DeRosse, Miklós Árgyelán et al. · 2018 · Biological Psychiatry
  41. Structural MRI-Based Predictions in Patients with Treatment-Refractory Depression (TRD)
    Blair A. Johnston, J. Douglas Steele, Serenella Tolomeo, David M. Christmas, Keith Matthews · 2015 · PLoS ONE
  42. Applying tensor-based morphometry to parametric surfaces can improve MRI-based disease diagnosis
    Yalin Wang, Lei Yuan, Jie Shi, Alexander Greve, Jieping Ye, Arthur W. Toga, Allan L. Reiss, Paul M. Thompson · 2013 · NeuroImage
  43. Slower Binocular Rivalry in the Autistic Brain
    Alina C. Spiegel, Jeff Mentch, Amanda J. Haskins, Caroline Elizabeth Robertson · 2019 · Current Biology
  44. Dyslexia detection using 3D convolutional neural networks and functional magnetic resonance imaging
    Sofia Zahia, Begonya García-Zapirain, Ibone Saralegui Prieto, B. Fernández-Ruanova · 2020 · Computer Methods and Programs in Biomedicine
  45. Multi-parameter machine learning approach to the neuroanatomical basis of developmental dyslexia
    P. Płoński, Wojciech Gradkowski, Irène Altarelli, Karla Monzalvo, Muna van Ermingen‐Marbach, Marion Grande, Stefan Heim, Artur Marchewka, Piotr Bogorodzki, Franck Ramus et al. · 2016 · Human Brain Mapping
  46. Multivariate Classification of Major Depressive Disorder Using the Effective Connectivity and Functional Connectivity
    Xiang-Fei GENG, Junhai Xu, Baolin Liu, Yonggang Shi · 2018 · Frontiers in Neuroscience
  47. Multimodal neuroimaging-based prediction of adult outcomes in childhood-onset ADHD using ensemble learning techniques
    Yuyang Luo, Tara L. Alvarez, Jeffrey M. Halperin, Xiaobo Li · 2020 · NeuroImage Clinical
  48. Deep-Asymmetry: Asymmetry Matrix Image for Deep Learning Method in Pre-Screening Depression
    Kang, Min, Kwon, Hyunjin, Park, Jin-Hyeok, Kang, Seokhwan, Lee, Youngho · 2020 · Sensors
  49. Accuracy of automated classification of major depressive disorder as a function of symptom severity
    Rajamannar Ramasubbu, Matthew Brown, Filomeno Cortese, Ismael Gaxiola‐Valdez, Bradley Gordon Goodyear, Andrew James Greenshaw, Serdar Murat Dursun, Russell Greiner · 2016 · NeuroImage Clinical
  50. An Autoencoder-Based Deep Learning Classifier for Efficient Diagnosis of Autism
    Harshini Sewani, Rasha F. Kashef · 2020 · Children
  51. Decision Support Algorithm for Diagnosis of ADHD Using Electroencephalograms
    Berdakh Abibullaev, Jinung An · 2011 · Journal of Medical Systems
  52. Separated Channel Attention Convolutional Neural Network (SC-CNN-Attention) to Identify ADHD in Multi-Site Rs-fMRI Dataset
    Tao Zhang, Cunbo Li, Peiyang Li, Yueheng Peng, Xiaodong Kang, Chenyang Jiang, Fali Li, Xuyang Zhu, Dezhong Yao, Bharat B. Biswal et al. · 2020 · Entropy
  53. Disease Definition for Schizophrenia by Functional Connectivity Using Radiomics Strategy
    Long‐Biao Cui, Lin Liu, Huaning Wang, Liuxian Wang, Fan Guo, Yibin Xi, Tingting Liu, Chen Li, Ping Tian, Kang Liu et al. · 2018 · Schizophrenia Bulletin
  54. Evaluating the diagnostic utility of applying a machine learning algorithm to diffusion tensor MRI measures in individuals with major depressive disorder
    David M. Schnyer, Peter C. Clasen, Christopher E. Gonzalez, Christopher G. Beevers · 2017 · Psychiatry Research Neuroimaging
  55. Classifying Major Depressive Disorder Using fNIRS During Motor Rehabilitation
    Yibo Zhu, Jagadish Kumaran Jayagopal, Ranjana K. Mehta, Madhav Erraguntla, Joseph K. Nuamah, Anthony D. McDonald, Heather B. Taylor, Shuo‐Hsiu Chang · 2020 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
  56. Deep Spatio-Temporal Representation and Ensemble Classification for Attention Deficit/Hyperactivity Disorder
    Shuaiqi Liu, Ling Zhao, Xu Wang, Xin Qi, Jie Zhao, David S. Guttery, Yudong Zhang · 2020 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
  57. Detecting brain structural changes as biomarker from magnetic resonance images using a local feature based SVM approach
    Ye Chen, Judd M. Storrs, Lirong Tan, Lawrence J. Mazlack, J. H. Lee, Long Jason Lu · 2013 · Journal of Neuroscience Methods
  58. Nodal centrality of functional network in the differentiation of schizophrenia
    Hu Cheng, Sharlene D. Newman, Joaquín Goñi, Jerillyn S. Kent, Josselyn M. Howell, Amanda R. Bolbecker, Aina Puce, Brian F. O’Donnell, William P. Hetrick · 2015 · Schizophrenia Research
  59. Functional network connectivity (FNC)-based generative adversarial network (GAN) and its applications in classification of mental disorders
    Jianlong Zhao, Jinjie Huang, Dongmei Zhi, Weizheng Yan, Xiaohong Ma, Xiao Yang, Xianbin Li, Qing Ke, Tianzi Jiang, Vince D. Calhoun et al. · 2020 · Journal of Neuroscience Methods
  60. Shared atypical default mode and salience network functional connectivity between autism and schizophrenia
    Heng Chen, Lucina Q. Uddin, Xujun Duan, Junjie Zheng, Zhiliang Long, Youxue Zhang, Xiaonan Guo, Yan Zhang, Jingping Zhao, Huafu Chen · 2017 · Autism Research
  61. Automated image quality evaluation of structural brain MRI using an ensemble of deep learning networks
    Sheeba J. Sujit, Ivan Coronado, Arash Kamali, Ponnada A. Narayana, Refaat E. Gabr · 2019 · Journal of Magnetic Resonance Imaging
  62. Functional connectivity networks in the autistic and healthy brain assessed using Granger causality
    Luca Pollonini, Udit Patidar, Ning Situ, Roozbeh Rezaie, Andrew C. Papanicolaou, George Zouridakis · 2010 · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
  63. A Neural Marker of Obsessive-Compulsive Disorder from Whole-Brain Functional Connectivity
    Yu Takagi, Yuki Sakai, Giuseppe Lisi, Noriaki Yahata, Yoshinari Abe, Seiji Nishida, Takashi Nakamae, Jun Morimoto, Mitsuo Kawato, Jin Narumoto et al. · 2017 · Scientific Reports
  64. ADHD classification by dual subspace learning using resting-state functional connectivity
    Ying Chen, Yibin Tang, Chun Wang, Xiaofeng Liu, Zhao Li, Zhishun Wang · 2020 · Artificial Intelligence in Medicine
  65. Ensemble Deep Learning on Large, Mixed-Site fMRI Datasets in Autism and Other Tasks
    Matthew Leming, J. M. Górriz, John Suckling A · 2020 · International Journal of Neural Systems
  66. Differential association of default mode network connectivity and rumination in healthy individuals and remitted MDD patients
    Giannis Lois, Michèle Wessa · 2016 · Social Cognitive and Affective Neuroscience
  67. Diagnostic model generated by MRI‐derived brain features in toddlers with autism spectrum disorder
    Xiang Xiao, Hui Fang, Jiansheng Wu, Chaoyong Xiao, Ting Xiao, Lu Qian, Fengjing Liang, Xiao Zhou, Kangkang Chu, Xiaoyan Ke · 2016 · Autism Research
  68. An EEG-based functional connectivity measure for automatic detection of alcohol use disorder
    Wajid Mumtaz, Mohamad Naufal bin Mohamad Saad, Nidal Kamel, Syed Saad Azhar Ali, Aamir Saeed Malik · 2017 · Artificial Intelligence in Medicine
  69. Attentional Connectivity-based Prediction of Autism Using Heterogeneous rs-fMRI Data from CC200 Atlas
    Yaya Liu, Lingyu Xu, Jun Li, Jie Yu, Xuan Yu · 2020 · Experimental Neurobiology
  70. Large-scale validation of the prediction model risk of bias assessment Tool (PROBAST) using a short form: high risk of bias models show poorer discrimination
    Esmée Venema, Benjamin S. Wessler, Jessica K. Paulus, Rehab Salah, Gowri Raman, Lester Y. Leung, Benjamin C. Koethe, Jason Nelson, Jinny G. Park, David V. Klaveren et al. · 2021 · Journal of Clinical Epidemiology
  71. EEG/ERP-based biomarker/neuroalgorithms in adults with ADHD: Development, reliability, and application in clinical practice
    Andreas Felix Müller, Sarah Vetsch, Ilia Pershin, Gian Candrian, Gian-Marco Baschera, Juri D. Kropotov, Johannes Kasper, Hossam Abdel Rehim, Dominique Eich · 2019 · The World Journal of Biological Psychiatry
  72. Identification of bipolar disorder using a combination of multimodality magnetic resonance imaging and machine learning techniques
    Hao Li, Liqian Cui, Liping Cao, Yizhi Zhang, Yueheng Liu, Wenhao Deng, Wenjin Zhou · 2020 · BMC Psychiatry
  73. IEEE Journal of Translational Engineering in Health and Medicine
    2023 · IEEE Journal of Translational Engineering in Health and Medicine
  74. Multikernel Capsule Network for Schizophrenia Identification
    Wang, Tian, Bezerianos, Anastasios, Cichocki, Andrzej, Li, Junhua · 2022 · IEEE Transactions on Cybernetics
  75. White Matter Connectome Edge Density in Children with Autism Spectrum Disorders: Potential Imaging Biomarkers Using Machine-Learning Models
    Seyedmehdi Payabvash, Eva M. Palacios, Julia P. Owen, Maxwell B. Wang, Teresa Tavassoli, Molly Rae Gerdes, Anne N. Brandes-Aitken, DANIEL J. CUNEO, Elysa J. Marco, Pratik Mukherjee · 2019 · Brain Connectivity
  76. Functional connectivity-based signatures of schizophrenia revealed by multiclass pattern analysis of resting-state fMRI from schizophrenic patients and their healthy siblings
    Yang Yu, Hui Shen, Huiran Zhang, Ling‐Li Zeng, Zhimin Xue, Dewen Hu · 2013 · BioMedical Engineering OnLine
  77. Diagnosing schizophrenia with network analysis and a machine learning method
    Young Tak Jo, Sung Woo Joo, Seung‐Hyun Shon, Harin Kim, Yangsik Kim, Jung Sun Lee · 2020 · International Journal of Methods in Psychiatric Research
  78. Attention Deficit Hyperactivity Disorder Diagnosis using non-linear univariate and multivariate EEG measurements: a preliminary study
    Maryam Rezaeezadeh, Sina Shamekhi, Mousa Shamsi · 2020 · Physical and Engineering Sciences in Medicine
  79. Structural and diffusion MRI based schizophrenia classification using 2D pretrained and 3D naive Convolutional Neural Networks
    Mengjiao Hu, Xing Qian, Siwei Liu, Amelia Jialing Koh, Kang Sim, Xudong Jiang, Cuntai Guan, Juan Helen Zhou · 2021 · Schizophrenia Research
  80. GAT-LI: a graph attention network based learning and interpreting method for functional brain network classification
    Jinlong Hu, Lijie Cao, Tenghui Li, Shoubin Dong, Ping Li · 2021 · BMC Bioinformatics
  81. Classification of schizophrenia using feature-based morphometry
    Umberto Castellani, E. Rossato, Vittorio Murino, Marcella Bellani, Gianluca Rambaldelli, Cinzia Perlini, Luisa Tomelleri, Michele Tansella, Paolo Brambilla · 2011 · Journal of Neural Transmission
  82. Applied Machine Learning Method to Predict Children With ADHD Using Prefrontal Cortex Activity: A Multicenter Study in Japan
    Akira Yasumura, Mikimasa Omori, Ayako Fukuda, Junichi Takahashi, Yukiko Yasumura, Eiji Nakagawa, Toshihide Koike, Yushiro Yamashita, Tasuku Miyajima, Tatsuya Koeda et al. · 2017 · Journal of Attention Disorders
  83. Multivariate Machine Learning Analyses in Identification of Major Depressive Disorder Using Resting-State Functional Connectivity: A Multicentral Study
    Yachen Shi, Linhai Zhang, Zan Wang, Xiang Lu, Tao Wang, Deyu Zhou, Zhijun Zhang · 2021 · ACS Chemical Neuroscience
  84. ADHD classification using auto-encoding neural network and binary hypothesis testing
    Yibin Tang, Jia Sun, Chun Wang, Yuan Zhong, Aimin Jiang, Gang Liu, Xiaofeng Liu · 2021 · Artificial Intelligence in Medicine
  85. Effects of spectral features of EEG signals recorded with different channels and recording statuses on ADHD classification with deep learning
    Mustafa Tosun · 2021 · Physical and Engineering Sciences in Medicine
  86. Abnormal neural activity as a potential biomarker for drug-naive first-episode adolescent-onset schizophrenia with coherence regional homogeneity and support vector machine analyses
    Yi Liu, Yan Zhang, Luxian Lv, Renrong Wu, Jingping Zhao, Wenbin Guo · 2017 · Schizophrenia Research
  87. Cortical thickness patterns as state biomarker of anorexia nervosa
    Luca Lavagnino, Benson Mwangi, Bo Cao, Megan E. Shott, Jair C. Soares, Guido Frank · 2018 · International Journal of Eating Disorders
  88. TE-HI-GCN: An Ensemble of Transfer Hierarchical Graph Convolutional Networks for Disorder Diagnosis
    Lanting Li, Hao Jiang, Guangqi Wen, Peng Cao, XU Ming-yi, Xiaoli Liu, Jinzhu Yang, Osmar R. Zai͏̈ane · 2021 · Neuroinformatics
  89. Decreased interhemispheric functional connectivity rather than corpus callosum volume as a potential biomarker for autism spectrum disorder
    Qin Li, Benjamin Becker, Xi Jiang, Zhiying Zhao, Qiong Zhang, Shuxia Yao, Keith Maurice Kendrick · 2019 · Cortex
  90. Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis
    Luigi A. Maglanoc, Tobias Kaufmann, Rune Jonassen, Eva Hilland, Dani Beck, Nils Inge Landrø, Lars Tjelta Westlye · 2019 · Human Brain Mapping
  91. Deep learning based automatic diagnosis of first-episode psychosis, bipolar disorder and healthy controls
    Zhuangzhuang Li, Wenmei Li, Yan Wei, Guan Gui, Rongrong Zhang, Haiyan Liu, Yu‐Chen Chen, Yiqiu Jiang · 2021 · Computerized Medical Imaging and Graphics
  92. Detection of ADHD From EEG Signals Using Different Entropy Measures and ANN
    R. Catherine Joy, Selvaraj Thomas George, A. Albert Rajan, M. S. P. Subathra · 2021 · Clinical EEG and Neuroscience
  93. Prefrontal activation during inhibitory control measured by near-infrared spectroscopy for differentiating between autism spectrum disorders and attention deficit hyperactivity disorder in adults
    Ayaka Ishii‐Takahashi, Ryu Takizawa, Yukika Nishimura, Yuki Kawakubo, Hitoshi Kuwabara, Junko Matsubayashi, Kasumi Hamada, Shiho Okuhata, Noriaki Yahata, Takashi Igarashi et al. · 2013 · NeuroImage Clinical
  94. Dynamic functional–structural coupling within acute functional state change phases: Evidence from a depression recognition study
    Kun Bi, Lingling Hua, Maobin Wei, Jiaolong Qin, Qing Lü, Zhijian Yao · 2015 · Journal of Affective Disorders
  95. Connectivity of the anterior insula differentiates participants with first-episode schizophrenia spectrum disorders from controls: a machine- learning study
    Mikolas, P., Melicher, T., Skoch, A., Matejka, M., Slovakova, A., Bakstein, E., Hajek, T., Spaniel, F. · 2016 · Psychological Medicine
  96. Whole-brain resting-state functional connectivity identified major depressive disorder: A multivariate pattern analysis in two independent samples
    Xue Bing Zhong, Huqing Shi, Qingsen Ming, Daifeng Dong, Xiaocui Zhang, Ling‐Li Zeng, Shuqiao Yao · 2017 · Journal of Affective Disorders
  97. Distinctive Neuroanatomical Substrates for Depression in Bipolar Disorder versus Major Depressive Disorder
    Koji Matsuo, Kenichiro Harada, Yusuke Fujita, Yasumasa Okamoto, Miho Ota, Hisashi Narita, Benson Mwangi, Carlos A Gutierrez, Go Okada, Masahiro Takamura et al. · 2017 · Cerebral Cortex
  98. Multisite generalizability of schizophrenia diagnosis classification based on functional brain connectivity
    Pierre Orban, Christian L. Dansereau, Laurence Desbois, Violaine Mongeau‐Pérusse, Charles‐Édouard Giguère, Hien D. Nguyen, Adrianna Mendrek, Émmanuel Stip, Pierre Bellec · 2017 · Schizophrenia Research
  99. Phase Space Reconstruction of EEG Signals for Classification of ADHD and Control Adults
    Simranjit Kaur, Sukhwinder Singh, Priti Arun, Damanjeet Kaur, Manoj Kumar Bajaj · 2019 · Clinical EEG and Neuroscience
  100. Predicting alcohol use disorder remission: a longitudinal multimodal multi-featured machine learning approach
    Sivan Kinreich, Vivia V. McCutcheon, Fazil Alıev, Jacquelyn Leigh Meyers, Chella Kamarajan, Ashwini Kumar Pandey, David Balin Chorlian, Jian Zhang, Weipeng Kuang, Gayathri Pandey et al. · 2021 · Translational Psychiatry
  101. Shared and distinct resting functional connectivity in children and adults with attention-deficit/hyperactivity disorder
    Xiaojie Guo, Dongren Yao, Qingjiu Cao, Lu Liu, Qihua Zhao, Hui Li, Fang Huang, Yanfei Wang, Qiujin Qian, Yufeng Wang et al. · 2020 · Translational Psychiatry
  102. Screening of autism based on task-free fMRI using graph theoretical approach
    Masoumeh Sadeghi, Reza Khosrowabadi, Fatemeh Bakouie, Hoda Mahdavi, Changiz Eslahchi, Hamidreza Pouretemad · 2017 · Psychiatry Research Neuroimaging
  103. Functional EEG connectivity is a neuromarker for adult attention deficit hyperactivity disorder symptoms
    Hanni S. M. Kiiski, Laura M. Rueda‐Delgado, Marc Bennett, Rachel Knight, Laura A. Rai, Darren William Roddy, Katie Grogan, Jessica Bramham, Clare A. M. Kelly, Robert Whelan · 2019 · Clinical Neurophysiology
  104. Aberrant functional connectivity for diagnosis of major depressive disorder: A discriminant analysis
    Longlong Cao, Shuixia Guo, Zhimin Xue, Yong Hu, Haihong Liu, Tumbwene Elieza Mwansisya, Weidan Pu, Bo Yang, Chang Liu, Jianfeng Feng et al. · 2013 · Psychiatry and Clinical Neurosciences
  105. Gray Matter Alterations in Young Children with Autism Spectrum Disorders: Comparing Morphometry at the Voxel and Regional Level
    Ilaria Gori, Alessia Giuliano, Filippo Muratori, Irene Saviozzi, P. Oliva, Raffaella Tancredi, Angela Cosenza, Michela Tosetti, Sara Calderoni, Alessandra Retico · 2015 · Journal of Neuroimaging
  106. Diagnostic Classification of Schizophrenia Patients on the Basis of Regional Reward-Related fMRI Signal Patterns
    Stefan Koch, Claudia Hägele, John­–Dylan Haynes, Andreas Heinz, Florian Schlagenhauf, Philipp Sterzer · 2015 · PLoS ONE
  107. Network-based classification of ADHD patients using discriminative subnetwork selection and graph kernel PCA
    Junqiang Du, Lipeng Wang, Biao Jie, Dao-Qiang Zhang · 2016 · Comput. Medical Imaging Graph.
  108. A support vector machine model provides an accurate transcript-level-based diagnostic for major depressive disorder
    Jessica S. Yu, Albert Xue, Eva E. Redei, Neda Bagheri · 2016 · Translational Psychiatry
  109. Automatic schizophrenic discrimination on fNIRS by using complex brain network analysis and SVM
    Hong Song, Lei Chen, RuiQi Gao, Iordachescu Ilie Mihaita Bogdan, Jian Yang, Shuliang Wang, Wentian Dong, Wenxiang Quan, Weimin Dang, Xin Yu · 2017 · BMC Medical Informatics and Decision Making
  110. Surface-based shared and distinct resting functional connectivity in attention-deficit hyperactivity disorder and autism spectrum disorder
    Minyoung Jung, Yiheng Tu, Joel Park, Kristen Jorgenson, Courtney Lang, Wenwen Song, Jian Kong · 2018 · The British Journal of Psychiatry
  111. Prediction in Autism by Deep Learning Short-Time Spontaneous Hemodynamic Fluctuations
    Lingyu Xu, Xiulin Geng, Xiaoyu He, Jun Li, Jie Yu · 2019 · Frontiers in Neuroscience
  112. Differences in atypical resting-state effective connectivity distinguish autism from schizophrenia
    Dana Mastrovito, Catherine Hanson, Stephen José Hanson · 2018 · NeuroImage Clinical
  113. Diagnosis of autism spectrum disorder based on complex network features
    Ghasem Sadeghi Bajestani, Mahboobe Behrooz, Adel Ghazi Khani, Mostafa Nouri-Baygi, Ali Mollaei · 2019 · Computer Methods and Programs in Biomedicine
  114. Predicting depression based on dynamic regional connectivity: A windowed Granger causality analysis of MEG recordings
    Qing Lü, Kun Bi, Chu Liu, Guoping Luo, Hao Tang, Zhijian Yao · 2013 · Brain Research
  115. Classification of ADHD and BMD patients using visual evoked potential
    Adeleh Dehghani, Reza Boostani, Somayeh Afrasiabi, Khadijeh Sadatnezhad · 2013 · Clinical Neurology and Neurosurgery
  116. Classification of Adolescent Major Depressive Disorder Via Static and Dynamic Connectivity
    Bhaskar Sen, Kathryn Regan Cullen, Keshab K. Parhi · 2020 · IEEE Journal of Biomedical and Health Informatics
  117. A self-learned decomposition and classification model for schizophrenia diagnosis
    Smith K. Khare, Varun Bajaj · 2021 · Computer Methods and Programs in Biomedicine
  118. Exploiting the brain's network structure in identifying ADHD subjects
    Soumyabrata Dey, A. Ravishankar Rao, Mubarak A. Shah · 2012 · Frontiers in Systems Neuroscience
  119. Assessment of Adherence to Reporting Guidelines by Commonly Used Clinical Prediction Models From a Single Vendor
    Jonathan Lu, Alison Callahan, Birju Patel, Keith Morse, Dev Dash, Michael A. Pfeffer, Nigam Haresh Shah · 2022 · JAMA Network Open
  120. Grey matter volume patterns in thalamic nuclei are associated with familial risk for schizophrenia
    Giulio Pergola, Silvestro Trizio, Pasquale Di Carlo, Paolo Taurisano, Marina Mancini, Nicola Amoroso, Maria Antonietta Nettis, Ileana Andriola, Grazia Caforio, Teresa Popolizio et al. · 2016 · Schizophrenia Research
  121. Enhancing the representation of functional connectivity networks by fusing multi‐view information for autism spectrum disorder diagnosis
    Huifang Huang, Xingdan Liu, Yan Jin, Seong–Whan Lee, Chong-yaw Wee A, Dinggang G. Shen · 2018 · Human Brain Mapping
  122. Towards interpretable machine learning models for diagnosis aid: A case study on attention deficit/hyperactivity disorder
    Sarah Itani, Mandy Rossignol, Fabian Lecron, Philippe Fortemps · 2019 · PLoS ONE
  123. A novel approach for automated alcoholism detection using Fourier decomposition method
    Virender Kumar Mehla, Amit Singhal, Pushpendra Singh · 2020 · Journal of Neuroscience Methods
  124. Mapping relationships among schizophrenia, bipolar and schizoaffective disorders: A deep classification and clustering framework using fMRI time series
    Weizheng Yan, Min Zhao, Zening Fu, Godfrey D. Pearlson, Jing Sui (Beijing Normal University), my correct affiliation is beijing normal university, not Qingdao University of Science and Technology, please correct the current affiliation. Thank you, Vince D. Calhoun · 2021 · Schizophrenia Research
  125. Robust features for the automatic identification of autism spectrum disorder in children
    Justin Eldridge, Alison Elizabeth Lane, Mikhail Belkin, Simon John Dennis · 2014 · Journal of Neurodevelopmental Disorders
  126. Multi-center machine learning in imaging psychiatry: A meta-model approach
    Petr Dluhoš, Daniel Schwarz, Wiepke Cahn, Neeltje E.M. van Haren, René S. Kahn, Filip Španiel, Jiřı́ Horáček, Tomáš Kašpárek, Hugo Gerard Schnack · 2017 · NeuroImage
  127. Functional, Anatomical, and Morphological Networks Highlight the Role of Basal Ganglia–Thalamus–Cortex Circuits in Schizophrenia
    Wei Dong Zhao, Shuixia Guo, Zeqiang Linli, Albert C. Yang, Ching‐Po Lin, Shih‐Jen Tsai · 2019 · Schizophrenia Bulletin
  128. A Multichannel Deep Neural Network Model Analyzing Multiscale Functional Brain Connectome Data for Attention Deficit Hyperactivity Disorder Detection
    Ming Chen, Hailong Li, Jing‐Hua Wang, Jonathan R. Dillman, Nehal A. Parikh, Lili He · 2019 · Radiology Artificial Intelligence
  129. Multivariate pattern analysis of obsessive–compulsive disorder using structural neuroanatomy
    Xinyu Hu, Qi Liu, Bin Li, Wanjie Tang, Huaiqiang Sun, Fei Yue Li, Yanchun Yang, Qiyong Gong, Xiaoqi Huang · 2015 · European Neuropsychopharmacology
  130. Divide and Conquer: Sub-Grouping of ASD Improves ASD Detection Based on Brain Morphometry
    Katuwal, Gajendra J., Baum, Stefi A., Cahill, Nathan D., Michael, Andrew M. · 2016 · PLOS ONE
  131. Machine learning classification of first-episode schizophrenia spectrum disorders and controls using whole brain white matter fractional anisotropy
    Pavol Mikoláš, Jaroslav Hlinka, Antonín Škoch, Zbyněk Pitra, Thomas Frodl, Filip Španiel, Tomáš Hájek · 2018 · BMC Psychiatry
  132. The Importance of Anti-correlations in Graph Theory Based Classification of Autism Spectrum Disorder
    Amirali Kazeminejad, Roberto Carlos Sotero · 2020 · Frontiers in Neuroscience
  133. Temporal variability of regional intrinsic neural activity in drug‐naïve patients with obsessive–compulsive disorder
    Jing Liu, Xuan Bu, Xinyu Hu, Hailong Li, Lingxiao Cao, Yingxue Gao, Kaili Liang, Lianqing Zhang, Lu Lu, Xinyue Hu et al. · 2021 · Human Brain Mapping
  134. Non-negative discriminative brain functional connectivity for identifying schizophrenia on resting-state fMRI
    Qi Zhu, Jiashuang Huang, Xijia Xu · 2018 · BioMedical Engineering OnLine
  135. Classifying and characterizing nicotine use disorder with high accuracy using machine learning and resting‐state fMRI
    Reagan R. Wetherill, Hengyi Rao, Nathan Hager, Jieqiong Wang, Teresa R. Franklin, Yong Fan A · 2018 · Addiction Biology
  136. Development and evaluation of a multimodal marker of major depressive disorder
    Jie Yang, Mengru Zhang, Hongshik Ahn, Qing Zhang, Tony B. Jin, Ien Li, Matthew David Nemesure, Nandita Joshi, Haoran Jiang, Jeffrey Morris Miller et al. · 2018 · Human Brain Mapping
  137. Identifying individuals with attention deficit hyperactivity disorder based on temporal variability of dynamic functional connectivity
    Xun‐Heng Wang, Yun Jiao, Lihua Li · 2018 · Scientific Reports
  138. Machine-learning-based classification between post-traumatic stress disorder and major depressive disorder using P300 features
    Miseon Shim, Min Jin Jin, Chang‐Hwan Im, Seung‐Hwan Lee · 2019 · NeuroImage Clinical
  139. Classification of schizophrenia patients through empirical wavelet transformation using electroencephalogram signals
    Smith K. Khare, Varun Bajaj, Siuly Siuly, G.R. Sinha · 2020 · Institute of Physics eBooks
  140. Machine Learning of Schizophrenia Detection with Structural and Functional Neuroimaging
    Dafa Shi, Yanfei Li, Haoran Zhang, Xiang Yao, Siyuan Wang, Guangsong Wang, Ke Ren · 2021 · Disease Markers
  141. Towards person-centered neuroimaging markers for resilience and vulnerability in Bipolar Disorder
    Sophia Frangou, Danai Dima, Jigar Jogia · 2016 · NeuroImage
  142. Discovering Alzheimer's disease and bipolar disorder white matter effects building computer aided diagnostic systems on brain diffusion tensor imaging features
    Ariadna Besga, Maite Termenón, Manuel Graña, J. Echeveste, J.M. Pérez, Ana María González-Pinto · 2012 · Neuroscience Letters
  143. Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model
    Laura Pina‐Camacho, Juan García-Prieto, Mara Parellada, Josefina Castro‐Fornieles, Ana María González-Pinto, Igor Bombín, Montserrat Graell, Beatriz Payá, Marta Rapado‐Castro, Joost Janssen et al. · 2014 · European Child & Adolescent Psychiatry
  144. Machine learning classifier using abnormal brain network topological metrics in major depressive disorder
    Guo, Hao, Cao, Xiaohua, Liu, Zhifen, Li, Haifang, Chen, Junjie, Zhang, Kerang · 2012 · NeuroReport
  145. Identifying ADHD children using hemodynamic responses during a working memory task measured by functional near-infrared spectroscopy
    Yue Gu, Shuo Miao, Junxia Han, Zhenhu Liang, Gaoxiang Ouyang, Jian Yang, Xiaoli Li A · 2017 · Journal of Neural Engineering
  146. Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach
    Mutlu Mete, Ünal Sakoğlu, Jeffrey S. Spence, Michael D. Devous, Thomas S. Harris, Bryon H. Adinoff · 2016 · BMC Bioinformatics
  147. Transdiagnostic differences in the resting-state functional connectivity of the prefrontal cortex in depression and schizophrenia
    Xi Chen, Chang Liu, Hui He, Xin Chang, Yuchao Jiang, Yingjia Li, Mingjun Duan, Jianfu Li, Cheng Luo, Dezhong Yao · 2017 · Journal of Affective Disorders
  148. Multiple functional networks modeling for autism spectrum disorder diagnosis
    Tae‐Eui Kam, Heung‐Il Suk, Seong–Whan Lee · 2017 · Human Brain Mapping
  149. Multimodal MR Images-Based Diagnosis of Early Adolescent Attention-Deficit/Hyperactivity Disorder Using Multiple Kernel Learning
    Xiaocheng Zhou, Qingmin Lin, Yuanyuan Gui, Zixin Wang, Manhua Liu, Hui Juan Lu · 2021 · Frontiers in Neuroscience
  150. Robust disruptions in electroencephalogram cortical oscillations and large-scale functional networks in autism
    Sean Matlis, Katica Boric, Catherine J. Chu, Mark Kramer · 2015 · BMC Neurology
  151. Machine-based classification of ADHD and nonADHD participants using time/frequency features of event-related neuroelectric activity
    Hüseyin Öztoprak, Mehmet Toycan, Yaşar Kemal, Orhan Arıkan, Elvin Doğutepe, Sirel Karakaş · 2017 · Clinical Neurophysiology
  152. Population Graph-Based Multi-Model Ensemble Method for Diagnosing Autism Spectrum Disorder
    Zarina Rakhimberdina, Xin Liu, Tsuyoshi Murata · 2020 · Sensors
  153. Identifying neuroanatomical signatures of anorexia nervosa: a multivariate machine learning approach
    Luca Lavagnino, Federico Amianto, Benson Mwangi, Federico D’Agata, Angela Valentina Spalatro, Giovana B. Zunta‐Soares, Giovanni Abbate Daga, Paolo Mortara, Secondo Fassino, Jair C. Soares · 2015 · Psychological Medicine
  154. Abnormalities in the effective connectivity of visuothalamic circuitry in schizophrenia
    Sarina Jennifer Iwabuchi, Lena K. Palaniyappan · 2017 · Psychological Medicine
  155. Detection of an Autism EEG Signature From Only Two EEG Channels Through Features Extraction and Advanced Machine Learning Analysis
    Enzo Grossi, Giovanni Valbusa, Massimo Buscema · 2020 · Clinical EEG and Neuroscience
  156. Identification of psychopathic individuals using pattern classification of MRI images
    João Ricardo Sato, Ricardo de Oliveira‐Souza, Carlos Eduardo Thomaz, Rodrigo Basílio, Ivanei Edson Bramati, Edson Amaro, Fernanda Freire Tovar-Moll, Robert D. Hare, Jorge Moll · 2011 · Social Neuroscience
  157. Automated classification of fMRI during cognitive control identifies more severely disorganized subjects with schizophrenia
    Jong H. Yoon, Danh V. Nguyen, Lindsey M. McVay, Paul J. Deramo, Michael Minzenberg, John Daniel Ragland, Tara A. Niendam, Marjorie Solomon, Cameron S. Carter · 2012 · Schizophrenia Research
  158. Predictive Neurofunctional Markers of Attention-Deficit/Hyperactivity Disorder Based on Pattern Classification of Temporal Processing
    Heledd C. Hart, André F. Marquand, Anna B Smith, Ana Cubillo, Andrew Simmons, Michael John Brammer, Katya Rubia · 2014 · Journal of the American Academy of Child & Adolescent Psychiatry
  159. Learning stable and predictive network-based patterns of schizophrenia and its clinical symptoms
    M. Gheiratmand, Irina Rish, Guillermo Cecchi, Matthew Robert Graham Brown, Russell Greiner, Pablo I. Polosecki, Pouya Bashivan, Andrew James Greenshaw, Rajamannar Ramasubbu, Serdar Murat Dursun · 2017 · Schizophrenia
  160. Differentiating Boys with ADHD from Those with Typical Development Based on Whole-Brain Functional Connections Using a Machine Learning Approach
    Yunkai Sun, Lei Zhao, Zhihui Lan, Xi-Ze Jia, Shao‐Wei Xue · 2020 · Neuropsychiatric Disease and Treatment
  161. Detecting Abnormal Brain Regions in Schizophrenia Using Structural MRI via Machine Learning
    Zhihong Chen, Tao Yan, Er-Lei Wang, Hong Jiang, Yi-Qian Tang, Xi Yu, Jian Zhang, Chang Liu · 2020 · Computational Intelligence and Neuroscience
  162. Diagnosis of Schizophrenia Based on Deep Learning Using fMRI
    JinChi Zheng, Xiaolan Wei, JinYi Wang, Huasong Lin, HongRun Pan, YuQing Shi · 2021 · Computational and Mathematical Methods in Medicine
  163. Abnormal Fractional Amplitude of Low-Frequency Fluctuation as a Potential Imaging Biomarker for First-Episode Major Depressive Disorder: A Resting-State fMRI Study and Support Vector Machine Analysis
    Yujun Gao, Xi Wang, Zhenying Xiong, Hongwei Ren, Ruoshi Liu, Yafen Wei, Dongbin Li · 2021 · Frontiers in Neurology
  164. Structural Features Related to Affective Instability Correctly Classify Patients With Borderline Personality Disorder. A Supervised Machine Learning Approach
    Alessandro Grecucci, Gaia Lapomarda, Irene Messina, Bianca Monachesi, Sara Sorella, Roma Šiugždaitė · 2022 · Frontiers in Psychiatry
  165. Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRI
    Youngoh Bae, Kunaraj Kumarasamy, Issa M. Ali, Panagiotis D. Korfiatis, Zeynettin Akkus, Bradley James Erickson · 2017 · Journal of Imaging Informatics in Medicine
  166. The Diagnosis of Autism Spectrum Disorder Based on the Random Neural Network Cluster
    Xia-an Bi, Yingchao Liu, Qin Jiang, Shu Qing Ma, Qi Sun, Jianhua Dai · 2018 · Frontiers in Human Neuroscience
  167. Multivariate classification of drug-naive obsessive-compulsive disorder patients and healthy controls by applying an SVM to resting-state functional MRI data
    Xi Yang, Xinyu Hu, Wanjie Tang, Bin Li, Yanchun Yang, Qiyong Gong, Xiaoqi Huang · 2019 · BMC Psychiatry
  168. Multimodal Integration of Brain Images for MRI-Based Diagnosis in Schizophrenia
    Raymond M. Salvador, Erick Jorge Canales-Rodríguez, Amalia Guerrero‐Pedraza, Salvador Sarró, Diana Tordesillas‐Gutiérrez, Teresa Maristany, Benedicto Crespo‐Facorro, Peter J. McKenna, Edith Pomarol‐Clotet · 2019 · Frontiers in Neuroscience
  169. Identifying commonality and specificity across psychosis sub-groups via classification based on features from dynamic connectivity analysis
    Yuhui Du, Hui Hao, Shuhua Wang, Godfrey D. Pearlson, Vince D. Calhoun · 2020 · NeuroImage Clinical
  170. Identification of autism spectrum disorder based on short-term spontaneous hemodynamic fluctuations using deep learning in a multi-layer neural network
    Lingyu Xu, Zhiyong Sun, Jiang Xie, Jie Yu, Jun Li, Jinhong Wang · 2020 · Clinical Neurophysiology
  171. Recognition of Schizophrenia with Regularized Support Vector Machine and Sequential Region of Interest Selection using Structural Magnetic Resonance Imaging
    Rowena Chin, Alex Xiaobin You, Fanwen Meng, Juan Helen Zhou, Kang Sim · 2018 · Scientific Reports
  172. Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder
    E. Schwarz, N. T. Doan, G. Pergola, L. Westlye, T. Kaufmann, T. Wolfers, Ralph Brecheisen, T. Quarto, Alex Ing, P. Di Carlo et al. · 2019 · Translational Psychiatry
  173. Automatic classification of schizophrenia patients using resting-state EEG signals
    Hossein Najaf-Zadeh, Mahdad Esmaeili, Sara Farhang, Yashar Sarbaz, Seyed Hossein Rasta · 2021 · Physical and Engineering Sciences in Medicine
  174. Classification of Schizophrenia and Depression by EEG with ANNs*
    Yingjie Li, Fei-yan Fan · 2005
  175. Automated network analysis to measure brain effective connectivity estimated from EEG data of patients with alcoholism
    Youngoh Bae, Byeong Wook Yoo, Jung Chan Lee, Hee Chan Kim · 2017 · Physiological Measurement
  176. Machine learning approach to identify a resting-state functional connectivity pattern serving as an endophenotype of autism spectrum disorder
    Bun Yamagata, Takashi Itahashi, Junya Fujino, Haruhisa Ohta, Motoaki Nakamura, Nobumasa Kato, Masaru Mimura, Ryu-ichiro Hashimoto, Yuta Y. Aoki · 2018 · Brain Imaging and Behavior
  177. EEG Connectivity Analysis Using Denoising Autoencoders for the Detection of Dyslexia
    Francisco J. Martínez-Murcia, Andrés Ortíz, J. M. Górriz, Javier Ramı́rez, Pedro Javier López-Pérez, Miguel López‐Zamora, Juan Luis Luque · 2020 · International Journal of Neural Systems
  178. EEG Source Network for the Diagnosis of Schizophrenia and the Identification of Subtypes Based on Symptom Severity—A Machine Learning Approach
    Jeong-Youn Kim, Hyun Seo Lee, Seung‐Hwan Lee · 2020 · Journal of Clinical Medicine
  179. Identification of Autism Subtypes Based on Wavelet Coherence of BOLD FMRI Signals Using Convolutional Neural Network
    Mohammed Isam Al-Hiyali, Norashikin Yahya, Ibrahima Faye, Ahmed Faeq Hussein · 2021 · Sensors
  180. Altered anatomical patterns of depression in relation to antidepressant treatment: Evidence from a pattern recognition analysis on the topological organization of brain networks
    Jiaolong Qin, Maobin Wei, Haiyan Liu, Jianhuai Chen, Rui Yan, Zhijian Yao, Qing Lü · 2015 · Journal of Affective Disorders
  181. Anxiety and Depression Diagnosis Method Based on Brain Networks and Convolutional Neural Networks
    Yunlong Xie, Banghua Yang, Xi Lu, Minmin Zheng, Cunxiu Fan, Xiaoying Bi, Shu Zhou, Yingjie Li · 2020 · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
  182. Diagnosing autism spectrum disorder using brain entropy: A fast entropy method
    Liangliang Zhang, Xun‐Heng Wang, Lihua Li · 2019 · Computer Methods and Programs in Biomedicine
  183. A robust DWT–CNN‐based CAD system for early diagnosis of autism using task‐based fMRI
    Reem T. Haweel, Ahmed M. Shalaby, Ali H. Mahmoud, Noha AbdElSabour Seada, Said Ghoniemy, Mohammed Asaad Ghazal, Manuel Fernando Casanova, Gregory Neal Barnes, Ayman S El-Baz · 2020 · Medical Physics
  184. Aiding diagnosis of attention‐deficit/hyperactivity disorder and its subtypes: discriminant function analysis of event‐related potential data
    Janette L. Smith, Stuart John Johnstone, Robert J. Barry · 2003 · Journal of Child Psychology and Psychiatry
  185. Large-Scale Brain Functional Network Integration for Discrimination of Autism Using a 3-D Deep Learning Model
    Ming–Hsuan Yang, Menglin Cao, Yuhao Chen, Yanni Chen, Geng Fan, Chenxi Li, Jue Wang, Tian Liu · 2021 · Frontiers in Human Neuroscience
  186. Distributed Intrinsic Functional Connectivity Patterns Predict Diagnostic Status in Large Autism Cohort
    Afrooz Jahedi, Chanond A. Nasamran, Brian Faires, Juanjuan Fan, Ralph‐Axel Müller · 2017 · Brain Connectivity
  187. Support Vector Machine Classification of Obsessive-Compulsive Disorder Based on Whole-Brain Volumetry and Diffusion Tensor Imaging
    Cong Zhou, Yuqi Cheng, Liangliang Ping, Jian Xu, Zonglin Shen, Linling Jiang, Li Shi, Shuran Yang, Yi Lü, Xiufeng Xu · 2018 · Frontiers in Psychiatry
  188. Characterizing and Predicting Autism Spectrum Disorder by Performing Resting-State Functional Network Community Pattern Analysis
    Yuqing Song, Thomas Martial Epalle, Hu Lu · 2019 · Frontiers in Human Neuroscience
  189. Examining Bias and Reporting in Oral Health Prediction Modeling Studies
    Mi Du, Dandara Gabriela Haag, Youngha Song, John William Lynch, Murthy Mittinty · 2020 · Journal of Dental Research
  190. Effective Connectivity in Default Mode Network for Alcoholism Diagnosis
    Danish Mahmood Khan, Norashikin Yahya, Nidal Kamel, Ibrahima Faye · 2021 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
  191. An integrated machine learning framework for a discriminative analysis of schizophrenia using multi-biological data
    Pengfei Ke, Dong-sheng Xiong, Jia-hui Li, Zhi-lin Pan, Jing Zhou, Shi-jia Li, Jie Song, Xiao-yi Chen, Gui-xiang Li, Jun Chen et al. · 2021 · Scientific Reports
  192. Task modulations and clinical manifestations in the brain functional connectome in 1615 fMRI datasets
    Tobias Kaufmann, Dag Alnæs, Christine Lycke Brandt, Nhat Trung Doan, Karolina Kauppi, Francesco Bettella, Trine Vik Lagerberg, Akiah Ottesen Berg, Srdjan Djurovic, Ingrid Agartz et al. · 2016 · NeuroImage
  193. Cross-network interaction for diagnosis of major depressive disorder based on resting state functional connectivity
    Xueling Zhu, Fulai Yuan, Gaofeng Zhou, Jilin Nie, Dongcui Wang, Ping Hu, Lirong Ouyang, Lingyu Kong, Weihua Liao · 2020 · Brain Imaging and Behavior
  194. Decreased integration of the frontoparietal network during a working memory task in major depressive disorder
    Wenjian Tan, Zhening Liu, Chang Xi, Mengjie Deng, Yicheng Long, Lena K. Palaniyappan, Jie Yang · 2020 · Australian & New Zealand Journal of Psychiatry
  195. The Utility of a Computerized Algorithm Based on a Multi-Domain Profile of Measures for the Diagnosis of Attention Deficit/Hyperactivity Disorder
    Alessandro Crippa, Christian Salvatore, Erika Molteni, Maddalena Mauri, Antonio Salandi, Sara Trabattoni, Carlo Virginio Agostoni, Massimo Molteni, Maria Nobile, Isabella Castiglioni · 2017 · Frontiers in Psychiatry
  196. Bi-Dimensional Approach Based on Transfer Learning for Alcoholism Pre-disposition Classification via EEG Signals
    Hongyi Zhang, Francisco H. S. Silva, Elene Firmeza Ohata, Aldísio G. Medeiros, Pedro P. Rebouças Filho · 2020 · Frontiers in Human Neuroscience
  197. An End-to-End Depression Recognition Method Based on EEGNet
    Bo Liu, Hongli Chang, Kang Peng, Xuenan Wang · 2022 · Frontiers in Psychiatry
  198. The blessing of Dimensionality: Feature Selection outperforms functional connectivity-based feature transformation to classify ADHD subjects from EEG patterns of phase synchronisation
    Ernesto Pereda, Miguel García-Torres, Belén Melián-Batista, Soledad Mañas, Leopoldo D. Méndez, Julián J. González · 2018 · PLoS ONE
  199. Diagnostic and Predictive Neuroimaging Biomarkers for Posttraumatic Stress Disorder
    Sigal Zilcha‐Mano, Xi Zhu, Benjamin Suarez‐Jimenez, Alison M. Pickover, Shachaf Tal, Sara Such, Caroline Marohasy, Marika Chrisanthopoulos, Chloe Salzman, Amit Lazarov et al. · 2020 · Biological Psychiatry Cognitive Neuroscience and Neuroimaging
  200. Autism Spectrum Disorder and Childhood Apraxia of Speech: Early Language-Related Hallmarks across Structural MRI Study
    Eugenia Conti, Alessandra Retico, Letizia Palumbo, Giovanna Spera, Paolo Bosco, Laura Biagi, Simona Fiori, Michela Tosetti, Paola Cipriani, Giovanni Cioni et al. · 2020 · Journal of Personalized Medicine